neural network architecture

AI, ML & Data Science - Artificial Intelligence (AI) - Academic Use - Acharjo - Generative AI Fundamentals

A Deep Dive Into the Inner Workings of Large Language Models: 🧠 Transformer Architecture Explained: The Brain Behind LLMs

December 6, 2022 - By Kinshuk Dutta

🔍 Introduction: Beyond Thought Simulation In our previous blog on Thought Generation in AI and NLP, we explored how modern AI systems can simulate reasoning, explanation, and creativity. At the heart of this capability lies a game-changing innovation in deep learning: the Transformer architecture. Originally introduced in the groundbreaking paper Attention is All You Need by Vaswani et al. in 2017, transformers have become the standard building block for nearly every large language model (LLM)—including GPT, BERT, PaLM, and Claude. This blog takes a hardcore technical deep dive into the full transformer architecture diagram you see above. Whether you’re a…

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AI, ML & Data Science - Neural Networks - Deep Learning - Machine Learning

Introduction to Neural Networks and Deep Learning with Real-World Use Cases: Deep Learning & Neural Network Basics

January 9, 2019 - By Kinshuk Dutta

🧠 What Are Neural Networks? At the heart of deep learning lies the neural network—a mathematical model inspired by the human brain’s structure. These networks are made up of layers of artificial neurons that pass information from one layer to the next. Each neuron receives input, performs a weighted computation, and passes it to the next layer through an activation function. Neural networks are particularly well-suited to learning non-linear relationships from data. They allow machines to detect intricate patterns in images, audio, or text—without explicitly being programmed for the task. A basic neural network includes an input layer, one or…

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